As the basis for theoretical findings in this paper, we outline three prior theoretical results: marginal prior distribution for deep linear neural network  [1]}, exact covariance of two-layer DGP with squared exponential kernel [2]}, and the random feature expansion of squared exponential kernel [3]}.
